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This paper proposes a novel method, called Ringdown Time-Domain Vector Fitting (RTD-VF), for estimating electromechanical modes in interconnected power systems. Such a method authentically extends, to the context of ringdown analysis, the well known Time-Domain Vector Fitting (TD-VF) method, which has already been successfully applied within other power systems areas. The proposed method is based on a state-space discretization framework which enables ringdown events to be effectively estimated when described as artificial unit impulse responses. Moreover, RTD-VF completely avoids the necessity to perform discrete Fourier transforms (DFTs) of ringdown data sequences. Three case studies are used to validate the proposed method. One of the examples considers a synthetic test signal, whereas the other two case studies consider actual ringdown data sets extracted from the North American Eastern Interconnection (NAEI) system and from the Brazilian Interconnected Power (BIP) system.

The customary approach to modelling voltage transformers (VT) at gas insulate substations (GIS) subject to Very Fast Transients Overvoltages (VFTOs) consists of using a capacitive element. However, this simplistic approach is unable to reproduce characteristic resonances and predict how transients propagate to the VT’s secondary winding. Multiport black-box passive rational models built upon frequency-domain measurements are instrumental to overcome these challenges. The adoption of S-Parameters is an alternative to black-box approaches based on Y-Parameters so as to consistently expand the measurement frequency range which is required to accurately capture the dynamics involved in VFTO phenomena up to 50 MHz at GIS facilities. We validate our results using an strategy that entails measuring, modeling and simulation upon a multiport extra-high voltage (EHV) VT. The proposed approach using S-Parameters leads to increased accuracy compared with the customary approaches using Y-Parameters or capacitive elements. We build two models estimated upon distinct frequency ranges to highlight the importance of extending the measurements into the MHz range so that time-domain simulations better reproduce VFTO characteristics. The black-box VT model thus obtained is incorporated into an actual 500 kV GIS model for transient simulations enabling the analysis of transient propagation between primary and secondary windings.

The separation of low-frequency electromechanical modes from spurious modes is a challenging problem in ambient data analysis performed by identification and signal processing techniques. In order to accurately extract all relevant dynamic properties from power system ambient measurement data, a filtering pre-processing step and high-order models are usually adopted during the identification process for an effective handling of noise, which may lead to the appearance of the so-called spurious modes into the identified system model. These spurious modes have no physical relevance, but they may present similar characteristics to the low-frequency electromechanical modes, affecting the accurate evaluation of the latter ones. Hence, this paper proposes a post-processing technique based on modal stabilization diagrams to distinguish low-frequency electromechanical modes and spurious modes from ambient data analysis. This proposed post-processing technique is applied in simulated and real measured ambient data with the purpose of estimating the dynamic properties of inter-area modes in large interconnected generation and transmission power systems (IPSs), as well as, global and local modes in active distribution networks (ADNs) with distributed generation (DG) based on synchronous generators.

Vector fitting (VF) algorithms have become popular and powerful tools for estimating models formed by rational basis function (RBF) expansions. In this paper, we first translate the well-known continuous time-domain VF method (cTD-VF) to a discrete time-domain framework. We denote this new domain VF method by dTD-VF. Differently from the cTD-VF, the dTD-VF formulation does not rely on a numerical approximation of convolution integrals and, as a result, it can be easily implemented with a variety of RBF sets. The second part of this paper shows that the proposed dTD-VF can also be transformed into a novel instrumental variable (IV)-dTD-VF technique, which is shown to have a guaranteed optimal solution at convergence. Moreover, this important optimality property does not depend on the nature of the noise that corrupts the data (for instance, if it is white or colored). Two case studies highlight the advantages of using the proposed methods. One of these examples consists of modeling the admittance characteristics of a power system implemented as a frequency-dependent network equivalent (FDNE).

This paper presents a nonlinear model for a hydraulic amplifier, a component of the governor in the speed control loop of hydroelectric power plants. The amplifier transforms the electrical signal of the controller into mechanical movement of the turbine components, including the switching characteristics. This model is used to propose, on the one hand, a Piecewise Affine (PWA) representation for the hydraulic amplifier, and, on the other hand, a methodology for estimating the model parameters using field measurements, which facilitates its practical implementation. This representation is referred to as semi-physical because the model parameters are closely related with the physical construction of the hydraulic amplifier components. Among the advantages of this PWA representation are the appropriate structuring for use in system identification methods, for estimating its parameters, and the existence of advanced control techniques that use this structure in controller design, thereby improving the load-frequency control performance. The paper concludes with a description of the results, including the parameters that were estimated by using the hydraulic amplifier model with PWA structure.